Humans judge other humans based on their face images, predicting personality traits (such as generosity, reliability), capabilities (intelligence, precision) even guessing professions (a teacher, a care-giver, a lawyer) from a face image alone. Psychological research has found a high degree of correlation in such judgments (different people interpreting the same face image in a similar manner). Moreover, psychological research has also found a certain degree of correlation between face appearances and ground truth or real-world performance (successful CEO, winning martial arts fighter, etc).
Psychologists, counselors, coaches, therapists gather information on one's personal traits and those of others to analyze and advise on interactions in the social and business domains. However, it is clear that different people have different judgment capabilities, some judgments may be pure prejudice, and in any case it is impractical to rely on human judgment to process high-volumes of data in an efficient and repeatable manner.
In the prior art, face image analysis techniques have been provided to detect the emotional state of a person—e.g. anger/happiness/sadness by tracking or recognizing an expression defined by certain deformation of the face image as measured for example from the relative distances between facial landmarks, e.g., as disclosed by US Patent application No. 2011/0141258 “emotion recognition method and system thereof”. In contrast, the present invention measures traits or fixed personality characteristics which do not change over time. Actually, a neutral expression is preferred, as non-neutral expression, in particular an extreme emotional state, may distort the usual appearance of the person being analyzed.
It is an object of the present invention to provide a system which is capable of predicting personality traits based on automated computerized or computer assisted analysis of that person's body images and in particular face images.
It is another an object of the present invention to provide an automated method of selecting personality traits and capabilities that can be predicted from face images and predicting such traits and capabilities from one or more face images.
It is yet another object of the present invention to mechanize the process of personality analysis and interaction management, using automated methods in the field of image analysis, video analysis, machine learning and natural language generation.
Other objects and advantages of the invention will become apparent as the description proceeds.